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Direction-based segmentation of retinal blood vessels

Capitolo di libro
Data di Pubblicazione:
2017
Abstract:
An unsupervised method is introduced for retinal blood vessels segmentation. The direction map is built by assigning to each pixel a discrete direction out of twelve possible ones. Under- and over-segmented images are obtained by applying two different threshold values to the direction map. Almost all foreground pixels in the under-segmented image can be taken as vessel pixels. Missing vessel pixels in the under-segmented image are recovered by using the over-segmented image. The method has been tested on the DRIVE dataset producing satisfactory results, and its performance has been compared to that of other unsupervised methods.
Tipologia CRIS:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
retinal image; blood vessel segmentation; direction map
Elenco autori:
SANNITI DI BAJA, Gabriella; Riccio, Daniel; Frucci, Maria; Serino, Luca
Autori di Ateneo:
FRUCCI MARIA
SERINO LUCA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/321108
Titolo del libro:
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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